wehub-resource-sync
36 lines
1.2 KiB
Python
36 lines
1.2 KiB
Python
#
|
|
# SPDX-FileCopyrightText: Copyright (c) 1993-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
|
|
# SPDX-License-Identifier: Apache-2.0
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
#
|
|
|
|
import numpy as np
|
|
import onnx
|
|
import onnx_graphsurgeon as gs
|
|
|
|
def main():
|
|
input0 = gs.Variable(name="input0", dtype=np.float32, shape=('n_rows', 8))
|
|
input1 = gs.Variable(name="input1", dtype=np.float32, shape=('n_rows', 8))
|
|
output = gs.Variable(name="output", dtype=np.float32, )
|
|
|
|
node = gs.Node(op="Concat", inputs=[input0, input1], outputs=[output], attrs={"axis": 0})
|
|
|
|
graph = gs.Graph(nodes=[node], inputs=[input0, input1], outputs=[output])
|
|
|
|
model = gs.export_onnx(graph)
|
|
onnx.save(model, "concat_layer.onnx")
|
|
|
|
if __name__ == '__main__':
|
|
main()
|